An automated framework for the statistical analysis and interpretation of the functional impact of SNP sets using regulatory datasets from the ENCODE, Roadmap Epigenomics and other projects. GenomeRunner prioritizes regulatory datasets most significantly enriched in SNP sets and visualizes the most significant enrichments, thus suggesting regulatory mechanisms that may be altered by them. In addition to prioritizing SNP set-specific regulatory enrichments (functional impact), GenomeRunner implements three novel approaches: 1) regulatory similarity analysis, aimed at identifying groups of SNP sets having similar functional impact; 2) differential regulatory analysis, developed to identify functional impact specific for a group of SNP sets; and 3) cell type regulatory enrichment analysis, designed to identify cell type specificity of the functional impact.
Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA; Department of Arthritis and Clinical Immunology, Oklahoma Medical Research Foundation, Okla-homa City, OK, USA; Department of Biochemistry and Molecular Biology, University of Oklahoma Health Sciences Cen-ter, Oklahoma City, OK, USA
GenomeRunner funding source(s)
This work was supported by the Virginia Commonwealth University start-up fund, the National Institute of Arthritis and Musculoskeletal and Skin Diseases (a subaward from grant # P30 AR053483), an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences (a subaward from grant # P30 GM103510), and the National Science Foundation (Grant # ACI-1345426) for partial funding of this work.